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Sports Analytics Manager Jobs (NOW HIRING)

Swish Analytics

Trading Analyst

San Francisco, CA · On-site +1

Company Overview Swish Analytics is a sports analytics, betting, and fantasy startup building the ... You will help manage and improve real-time pricing across a range of sports and market types, with ...

Swish Analytics

Trading Analyst

San Francisco, CA

Company Overview Swish Analytics is a sports analytics, betting, and fantasy startup building the ... You will help manage and improve real-time pricing across a range of sports and market types, with ...

AEG

Sports Trading Analyst

San Francisco, CA · On-site

$70K - $120K/yr

Company Overview Swish Analytics is a sports analytics, betting, and fantasy startup building the ... You will help manage and improve real-time pricing across a range of sports and market types, with ...

Versant Media

Company Description VERSANT is a leading force in news, sports and entertainment - home to iconic ... We're looking for a strategic and data-driven Product Analytics Manager to advance our streaming ...

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How much do sports analytics manager jobs pay per year?

As of Jun 5, 2026, the average yearly pay for sports analytics manager in the United States is $55,952.00, according to ZipRecruiter salary data. Most workers in this role earn between $38,000.00 and $60,000.00 per year, depending on experience, location, and employer.

What does a Sports Analytics Manager do?

A Sports Analytics Manager is responsible for collecting, analyzing, and interpreting data related to athletic performance, player statistics, and team strategies. They use advanced statistical methods and software to help teams make informed decisions about player recruitment, game tactics, and injury prevention. By turning complex data into actionable insights, they play a crucial role in enhancing a team's competitive edge. These professionals often collaborate with coaches, scouts, and executives to implement data-driven strategies across the organization.

What is the difference between Sports Analytics Manager vs Sports Data Analyst?

AspectSports Analytics ManagerSports Data Analyst
Required CredentialsBachelor's or Master's in Sports Management, Statistics, or related field; experience in analyticsBachelor's in Statistics, Data Science, or related field; strong analytical skills
Work EnvironmentLeads teams, manages projects, strategic planningAnalyzes data, prepares reports, supports decision-making
Employer & Industry UsageSports teams, leagues, sports analytics firmsSports teams, media outlets, analytics companies
Search & Comparison IntentUnderstanding managerial roles in sports analyticsEntry to mid-level data analysis roles in sports

The Sports Analytics Manager oversees analytics teams and strategic initiatives, while the Sports Data Analyst focuses on data collection, analysis, and reporting. The manager role involves leadership and planning, whereas the analyst role emphasizes technical data work. Both roles require strong analytical skills and relevant education, but differ in scope and responsibilities.

What are the key skills and qualifications needed to thrive as a Sports Analytics Manager, and why are they important?

To thrive as a Sports Analytics Manager, you need strong quantitative analysis skills, a background in statistics or data science, and typically a relevant degree such as in mathematics, statistics, or sports management. Familiarity with data analysis tools like R, Python, SQL, and sports analytics software is crucial, along with experience in data visualization platforms. Exceptional communication, problem-solving, and leadership abilities help translate complex data into actionable insights for coaches and executives. These skills drive data-informed decisions that enhance team performance, strategy, and competitive advantage.

What are some common challenges faced by a Sports Analytics Manager when integrating data-driven insights into coaching decisions?

A Sports Analytics Manager often encounters challenges when translating complex data insights into actionable recommendations that coaches and athletes can easily understand and trust. Bridging the gap between technical analytics and practical application requires strong communication skills and ongoing collaboration with coaching staff. Additionally, gaining buy-in from team members who may be skeptical about analytics, and ensuring data quality and relevance, are frequent hurdles. Overcoming these challenges involves building strong relationships, providing clear and compelling data visualizations, and demonstrating the tangible impact of analytics on team performance.
More about Sports Analytics Manager jobs
What cities are hiring for Sports Analytics Manager jobs? Cities with the most Sports Analytics Manager job openings:
What are the most commonly searched types of Sports Analytics jobs? The most popular types of Sports Analytics jobs are:
What states have the most Sports Analytics Manager jobs? States with the most job openings for Sports Analytics Manager jobs include:
What job categories do people searching Sports Analytics Manager jobs look for? The top searched job categories for Sports Analytics Manager jobs are:
Sports Analytics Manager jobs near you
Infographic showing various Sports Analytics Manager job openings in the United States as of May 2026, with employment types broken down into 84% Full Time, 15% Part Time, and 1% Contract. Highlights an 94% Physical, 2% Hybrid, and 4% Remote job distribution, with an average salary of $55,952 per year, or $26.9 per hour.
Senior Data Platform Engineer

Senior Data Platform Engineer

Swish Analytics

San Francisco, CA • On-site, Remote

$180K/yr

Full-time

Posted 8 days ago

Job description

Company Overview
Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We're looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and consumer/enterprise clients.
Role Overview
The Swish Analytics team is seeking a Senior Data Platform Engineer to have a direct impact on the data infrastructure of our core consumer and enterprise data offerings. We're a team passionate about accurate predictions and real-time data, and hope you find satisfaction in building new products with the latest and greatest technologies. This is a remote position.
Seniority: Solid Senior level (5-8 years experience)
Core Responsibilities:
  • Proficiency in Python: Expertise in writing scalable, efficient, and testable code using Python for data processing, automation, and building back-end components. Familiarity with popular Python libraries is a plus.
  • Cloud Platforms: Proficiency in cloud services such as Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure, including knowledge of their specific data tools (e.g., Redshift, S3, Azure Data Factory, BigQuery).
  • 24/7 monitoring, alerting, and incident response of enterprise database architecture.
  • Developing KPI's, SLA's, SLO's and strategy to achieve and improve database stability
  • Backup/recovery testing and disaster recovery planning
  • Developing performance testing strategy,
  • Query performance analysis and optimization.
  • Implement and maintain RDS Proxy and connection management strategies
  • Manage database environments from production, data streams, to "Big Data" analytics.
  • Create and maintain policy runbooks and documentation for company use.
  • Database security, access control, and compliance
  • Working with MySQL/Postgres, Redshift, Kafka, Athena, Redis/Valkey, S3 and similar
  • Own schema migration tooling and process development

Skills Guide:
  • Operational Excellence: Monitoring (CloudWatch, Performance Insights, Datadog), alerting, on-call experience
  • MySQL Operations: Deep knowledge of RDS operational functions, performance tuning (indexes, query optimization, explain plans) Backup/restore, point-in-time recovery, replication troubleshooting
  • SQL Mastery: Proficiently writing and understanding complex SQL queries, including joins, subqueries, aggregations, and window functions.
  • Database Design Principles: Knowledge of normalization, denormalization, and how table structure impacts query performance.
  • Indexing: Understanding different index types (B-tree, hash, clustered, non-clustered) and their appropriate use for optimizing search and retrieval.
  • Automation: Software development for operational tasks
  • AWS: RDS operations, Authentication, Authorization
  • Incident Management: Root cause analysis, postmortem creation, Run book development

Nice to Have:
  • Performance testing tools (sysbench, HammerDB)
  • Execution Plan Analysis: Ability to read and interpret query execution plans to identify bottlenecks, such as full table scans, inefficient joins, or missing indexes.
  • Identifying Resource Bottlenecks: Pinpointing where queries are consuming excessive CPU, I/O, connections, or memory.

Base salary: Starting at $180,000+ - DOE
Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law. The position responsibilities are not limited to the responsibilities outlined above and are subject to change. At the employer's discretion, this position may require successful completion of background and reference checks.
Department Engineering & Infrastructure Locations San Francisco, CA - Remote Remote status Fully Remote

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